: This paper describes the development of neural network models for noise reduction. The networks used to enhance the performance of modeling captured signals by reducing the effec...
Because uncertain reasoning is often intractable, it is hard to reason with a large amount of knowledge. One solution to this problem is to specify a set of possible models, some s...
Charles A. Sutton, Brendan Burns, Clayton T. Morri...
In this paper, we present several enhanced network techniques which are appropriate for VLSI implementation and have reduced complexity, high throughput, and simple routing algori...
In this paper, we present the evolution of adaptive resonance theory (ART) neural network architectures (classifiers) using a multiobjective optimization approach. In particular, w...
Assem Kaylani, Michael Georgiopoulos, Mansooreh Mo...
Automakers are still facing an increasing complexity in vehicle requirements with regard to their EE systems. This complexity is not only caused by innovations, which are being pr...